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Evolution of computational models in BioModels Database and the Physiome Model Repository
Martin Scharm1, Tom Gebhardt2, Vasundra Touré3
1Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, 18051, Germany. martin.scharm@uni-rostock.de.
BMC Systems Biology
|April 14, 2018
Summary
Model reuse is common, with continuous updates improving annotations and information gain. Transparent documentation of model changes and provenance is crucial for trust and avoiding repeated errors in scientific modeling.
Area of Science:
- Computational Biology
- Systems Biology
- Bioinformatics
Background:
- Model reuse is essential for scientific progress, but modifications during reuse can alter interpretation.
- Lack of transparency in model changes hinders trust and effective reuse.
- Identifying and tracing model evolution is critical for understanding scientific development.
Purpose of the Study:
- To investigate the frequency and types of updates in biological models.
- To develop tools for visualizing and tracing changes in model repositories.
- To highlight the importance of transparent model provenance for scientific reuse.
Main Methods:
- Analyzed 13,734 models from BioModels Database and Physiome Model Repository.
- Studied update frequencies and types between model releases.
- Developed the MoSt tool for visualizing model changes and evolutionary statistics.
Main Results:
- Observed continuous updates in the majority of analyzed models, including early ones.
- Many updates target model annotations, enhancing information retrieval.
- Developed MoSt tool, with scripts and Docker image available for public use.
Conclusions:
- Transparent documentation and provenance of model changes are vital for building trust in model reuse.
- Understanding model evolution aids in avoiding past mistakes and gaining deeper scientific insights.
- Model repository maintainers should prioritize offering transparent model provenance.
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